In [1]:
In [2]:
In [3]:
CabData dataset has 359392 entries , 7 features and 0 missing values

Feature's datatypes

Transaction ID      int64
Date of Travel      int64
Company            object
City               object
KM Travelled      float64
Price Charged     float64
Cost of Trip      float64
dtype: object
Out[3]:
Transaction ID Date of Travel Company City KM Travelled Price Charged Cost of Trip
0 10000011 42377 Pink Cab ATLANTA GA 30.45 370.95 313.635
1 10000012 42375 Pink Cab ATLANTA GA 28.62 358.52 334.854
2 10000013 42371 Pink Cab ATLANTA GA 9.04 125.20 97.632
3 10000014 42376 Pink Cab ATLANTA GA 33.17 377.40 351.602
4 10000015 42372 Pink Cab ATLANTA GA 8.73 114.62 97.776
5 10000016 42376 Pink Cab ATLANTA GA 6.06 72.43 63.024
6 10000017 42372 Pink Cab AUSTIN TX 44.00 576.15 475.200
7 10000018 42376 Pink Cab AUSTIN TX 35.65 466.10 377.890
8 10000019 42381 Pink Cab BOSTON MA 14.40 191.61 146.880
9 10000020 42375 Pink Cab BOSTON MA 10.89 156.98 113.256
In [4]:
City dataset has 20 entries , 3 features and 0 missing values

Feature's datatypes

City          object
Population    object
Users         object
dtype: object
Out[4]:
City Population Users
0 NEW YORK NY 8,405,837 302,149
1 CHICAGO IL 1,955,130 164,468
2 LOS ANGELES CA 1,595,037 144,132
3 MIAMI FL 1,339,155 17,675
4 SILICON VALLEY 1,177,609 27,247
5 ORANGE COUNTY 1,030,185 12,994
6 SAN DIEGO CA 959,307 69,995
7 PHOENIX AZ 943,999 6,133
8 DALLAS TX 942,908 22,157
9 ATLANTA GA 814,885 24,701
10 DENVER CO 754,233 12,421
11 AUSTIN TX 698,371 14,978
12 SEATTLE WA 671,238 25,063
13 TUCSON AZ 631,442 5,712
14 SAN FRANCISCO CA 629,591 213,609
15 SACRAMENTO CA 545,776 7,044
16 PITTSBURGH PA 542,085 3,643
17 WASHINGTON DC 418,859 127,001
18 NASHVILLE TN 327,225 9,270
19 BOSTON MA 248,968 80,021
In [5]:
CustomerID dataset has 49171 entries , 4 features and 0 missing values

Feature's datatypes

Customer ID            int64
Gender                object
Age                    int64
Income (USD/Month)     int64
dtype: object
Out[5]:
Customer ID Gender Age Income (USD/Month)
0 29290 Male 28 10813
1 27703 Male 27 9237
2 28712 Male 53 11242
3 28020 Male 23 23327
4 27182 Male 33 8536
5 27318 Male 25 13984
6 33788 Male 23 23788
7 34106 Male 19 19980
8 59799 Male 33 19271
9 57982 Male 57 5068
In [6]:
TransactionID dataset has 440098 entries , 3 features and 0 missing values

Feature's datatypes

Transaction ID     int64
Customer ID        int64
Payment_Mode      object
dtype: object
Out[6]:
Transaction ID Customer ID Payment_Mode
0 10000011 29290 Card
1 10000012 27703 Card
2 10000013 28712 Cash
3 10000014 28020 Cash
4 10000015 27182 Card
5 10000016 27318 Cash
6 10000017 33788 Card
7 10000018 34106 Card
8 10000019 59799 Cash
9 10000020 57982 Cash
In [7]:
MasterData dataset has 359392 entries , 14 features and 0 missing values

Feature's datatypes

Transaction ID          int64
Date of Travel          int64
Company                object
City                   object
KM Travelled          float64
Price Charged         float64
Cost of Trip          float64
Customer ID             int64
Payment_Mode           object
Gender                 object
Age                     int64
Income (USD/Month)      int64
Population             object
Users                  object
dtype: object
Out[7]:
Transaction ID Date of Travel Company City KM Travelled Price Charged Cost of Trip Customer ID Payment_Mode Gender Age Income (USD/Month) Population Users
0 10000011 42377 Pink Cab ATLANTA GA 30.45 370.95 313.6350 29290 Card Male 28 10813 814,885 24,701
1 10351127 43302 Yellow Cab ATLANTA GA 26.19 598.70 317.4228 29290 Cash Male 28 10813 814,885 24,701
2 10412921 43427 Yellow Cab ATLANTA GA 42.55 792.05 597.4020 29290 Card Male 28 10813 814,885 24,701
3 10000012 42375 Pink Cab ATLANTA GA 28.62 358.52 334.8540 27703 Card Male 27 9237 814,885 24,701
4 10320494 43211 Yellow Cab ATLANTA GA 36.38 721.10 467.1192 27703 Card Male 27 9237 814,885 24,701
5 10324737 43224 Yellow Cab ATLANTA GA 6.18 138.40 87.5088 27703 Cash Male 27 9237 814,885 24,701
6 10395626 43400 Pink Cab ATLANTA GA 13.39 167.03 141.9340 27703 Card Male 27 9237 814,885 24,701
7 10000013 42371 Pink Cab ATLANTA GA 9.04 125.20 97.6320 28712 Cash Male 53 11242 814,885 24,701
8 10079404 42634 Yellow Cab ATLANTA GA 39.60 704.30 494.2080 28712 Card Male 53 11242 814,885 24,701
9 10186994 42909 Yellow Cab ATLANTA GA 18.19 365.63 246.6564 28712 Card Male 53 11242 814,885 24,701
In [8]:
Out[8]:
Transaction_ID Date_of_Travel Company City KM_Travelled Price_Charged Cost_of_Trip Customer_ID Payment_Mode Gender Age Income_(USD/Month) Population Users
0 10000011 42377 Pink Cab ATLANTA GA 30.45 370.95 313.6350 29290 Card Male 28 10813 814885 24701
1 10351127 43302 Yellow Cab ATLANTA GA 26.19 598.70 317.4228 29290 Cash Male 28 10813 814885 24701
2 10412921 43427 Yellow Cab ATLANTA GA 42.55 792.05 597.4020 29290 Card Male 28 10813 814885 24701
3 10000012 42375 Pink Cab ATLANTA GA 28.62 358.52 334.8540 27703 Card Male 27 9237 814885 24701
4 10320494 43211 Yellow Cab ATLANTA GA 36.38 721.10 467.1192 27703 Card Male 27 9237 814885 24701
5 10324737 43224 Yellow Cab ATLANTA GA 6.18 138.40 87.5088 27703 Cash Male 27 9237 814885 24701
6 10395626 43400 Pink Cab ATLANTA GA 13.39 167.03 141.9340 27703 Card Male 27 9237 814885 24701
7 10000013 42371 Pink Cab ATLANTA GA 9.04 125.20 97.6320 28712 Cash Male 53 11242 814885 24701
8 10079404 42634 Yellow Cab ATLANTA GA 39.60 704.30 494.2080 28712 Card Male 53 11242 814885 24701
9 10186994 42909 Yellow Cab ATLANTA GA 18.19 365.63 246.6564 28712 Card Male 53 11242 814885 24701
In [9]:
Feature's datatypes

Transaction_ID                 int64
Date_of_Travel        datetime64[ns]
Company                     category
City                        category
KM_Travelled                 float64
Price_Charged                float64
Cost_of_Trip                 float64
Customer_ID                    int64
Payment_Mode                category
Gender                      category
Age                            int64
Income_(USD/Month)             int64
Population                     int64
Users                          int64
dtype: object
In [10]:
In [11]:
Out[11]:
KM_Travelled Price_Charged Cost_of_Trip Age Income_(USD/Month) Population Users
count 84711.000000 84711.000000 84711.000000 84711.000000 84711.000000 8.471100e+04 84711.000000
mean 22.559917 310.800856 248.148682 35.322414 15059.047137 2.350642e+06 125590.813330
std 12.231092 181.995661 135.403345 12.644780 7991.077762 2.734890e+06 94593.433659
min 1.900000 15.600000 19.000000 18.000000 2000.000000 2.489680e+05 3643.000000
25% 12.000000 159.970000 131.868000 25.000000 8371.000000 8.148850e+05 27247.000000
50% 22.440000 298.060000 246.330000 33.000000 14713.000000 1.595037e+06 144132.000000
75% 32.960000 441.505000 360.180000 42.000000 21055.000000 1.955130e+06 164468.000000
max 48.000000 1623.480000 576.000000 65.000000 35000.000000 8.405837e+06 302149.000000
In [12]:
Out[12]:
KM_Travelled Price_Charged Cost_of_Trip Age Income_(USD/Month) Population Users
count 274681.000000 274681.000000 274681.000000 274681.000000 274681.000000 2.746810e+05 274681.000000
mean 22.569517 458.181990 297.922004 35.341112 15045.669817 3.373228e+06 168473.246981
std 12.234298 288.386166 162.548986 12.578625 7962.727062 3.439014e+06 100570.558886
min 1.900000 20.730000 22.800000 18.000000 2000.000000 2.489680e+05 3643.000000
25% 11.990000 226.680000 158.400000 25.000000 8439.000000 6.712380e+05 80021.000000
50% 22.440000 425.060000 295.596000 33.000000 14676.000000 1.595037e+06 144132.000000
75% 32.960000 633.880000 432.432000 42.000000 21023.000000 8.405837e+06 302149.000000
max 48.000000 2048.030000 691.200000 65.000000 34996.000000 8.405837e+06 302149.000000
In [13]:
Out[13]:
<AxesSubplot:xlabel='Income_(USD/Month)', ylabel='Count'>
In [14]:
Out[14]:
<AxesSubplot:xlabel='KM_Travelled', ylabel='Count'>
In [15]:
Out[15]:
<AxesSubplot:xlabel='Users', ylabel='Count'>
In [16]:
In [17]:
Statistical infos of Pink Cab Firm :


mean of : KM_Travelled is 22.559916775861275
median of : KM_Travelled is 22.44
median/mean ratio of : KM_Travelled is 0.9946845204681968
Q1 value of : KM_Travelled is 12.0
Q3 value of : KM_Travelled is 32.96
IQR value of : KM_Travelled is 20.96
Upper and Lower Limits of KM_Travelled is (-19.44, 64.4)

KM_Travelled has 0 outliers : []


**********************************************************



mean of : Price_Charged is 310.80085620521635
median of : Price_Charged is 298.06
median/mean ratio of : Price_Charged is 0.9590063670969948
Q1 value of : Price_Charged is 159.97
Q3 value of : Price_Charged is 441.505
IQR value of : Price_Charged is 281.53499999999997
Upper and Lower Limits of Price_Charged is (-262.3325, 863.8074999999999)

Price_Charged has 237 outliers : [ 902.65  870.48  896.35  901.07  869.94  891.22  901.71 1078.86  953.
  885.4   880.62  903.42  905.8   889.1  1105.72  880.57  910.33  954.04
  997.84 1021.72  983.99  870.29 1022.59  865.58  877.99 1014.03  977.81
  870.15  911.85  942.39  867.5   876.05  998.15  905.57  902.75  985.04
  904.36 1069.03  992.    884.49 1133.03  932.53 1517.15 1495.6   936.29
  894.83 1368.66 1234.24  951.53 1623.48 1319.52 1339.31 1094.02  893.57
 1172.53 1055.64 1106.11 1203.14 1045.77 1003.77  867.71  892.56 1050.27
 1359.59 1377.73 1222.2  1201.89 1122.32  956.67  881.71 1332.98  880.9
  864.94  883.72 1235.96 1020.1  1079.21  963.78  886.72  892.03  889.99
  991.19  884.69  872.03  962.44  940.66  981.86  886.06  933.06  870.21
  869.07  882.31  885.89 1016.03  883.95  950.98  931.1   951.95  884.13
  894.58  980.82  873.1  1076.93 1015.    891.93  901.16 1043.41  908.94
  952.95  937.8   919.68  999.55  920.72  954.99  891.11  891.06  864.3
  884.86  873.83  881.01  880.83 1002.14  864.16  893.04  898.1   868.29
 1052.66 1059.3   893.78  947.97  886.77 1020.77  995.24  902.67  865.12
  909.54  908.52  904.9   890.61  870.32 1170.67  875.14  929.63  957.39
 1002.97  894.04  881.26 1004.46  920.86  876.31  876.51 1001.28  877.3
  938.25  886.35  938.8   865.68  884.07  903.25  913.73  931.09  923.46
  865.71  924.62 1111.39  930.02  933.64 1033.82  889.31  882.04  970.74
 1016.55 1061.48  997.71  907.93  963.96  999.49  893.6   867.08  878.8
  977.46  868.87  872.25  960.06  973.38  898.7   893.78  872.23  928.92
  934.88  954.45  999.11  892.47  939.78  946.4   977.81  914.76  919.12
  900.    914.6  1150.62  898.54  885.63  881.83  980.1   909.38  901.25
  868.19 1010.32  891.39  943.9   868.9   942.19  873.5   978.27  943.37
  874.55  873.64  909.87  930.74  874.86  967.16  866.79  906.48  887.46
  953.62  891.84  864.15  894.8   916.57  867.1  1059.84  963.74 1019.75
 1166.86  873.95  912.87]


**********************************************************



mean of : Cost_of_Trip is 248.14868209559984
median of : Cost_of_Trip is 246.33
median/mean ratio of : Cost_of_Trip is 0.9926709983698435
Q1 value of : Cost_of_Trip is 131.868
Q3 value of : Cost_of_Trip is 360.18
IQR value of : Cost_of_Trip is 228.312
Upper and Lower Limits of Cost_of_Trip is (-210.60000000000002, 702.648)

Cost_of_Trip has 0 outliers : []


**********************************************************



mean of : Age is 35.322413854162974
median of : Age is 33.0
median/mean ratio of : Age is 0.9342509868167104
Q1 value of : Age is 25.0
Q3 value of : Age is 42.0
IQR value of : Age is 17.0
Upper and Lower Limits of Age is (-0.5, 67.5)

Age has 0 outliers : []


**********************************************************



mean of : Income_(USD/Month) is 15059.04713673549
median of : Income_(USD/Month) is 14713.0
median/mean ratio of : Income_(USD/Month) is 0.9770206485447985
Q1 value of : Income_(USD/Month) is 8371.0
Q3 value of : Income_(USD/Month) is 21055.0
IQR value of : Income_(USD/Month) is 12684.0
Upper and Lower Limits of Income_(USD/Month) is (-10655.0, 40081.0)

Income_(USD/Month) has 0 outliers : []


**********************************************************



mean of : Population is 2350641.5083165113
median of : Population is 1595037.0
median/mean ratio of : Population is 0.6785539157531247
Q1 value of : Population is 814885.0
Q3 value of : Population is 1955130.0
IQR value of : Population is 1140245.0
Upper and Lower Limits of Population is (-895482.5, 3665497.5)

Population has 13967 outliers : [8405837 8405837 8405837 ... 8405837 8405837 8405837]


**********************************************************



mean of : Users is 125590.81333002797
median of : Users is 144132.0
median/mean ratio of : Users is 1.1476317110969687
Q1 value of : Users is 27247.0
Q3 value of : Users is 164468.0
IQR value of : Users is 137221.0
Upper and Lower Limits of Users is (-178584.5, 370299.5)

Users has 0 outliers : []


**********************************************************

In [18]:
Statistical infos of Yellow Cab Firm :


mean of : KM_Travelled is 22.56951689414197
median of : KM_Travelled is 22.44
median/mean ratio of : KM_Travelled is 0.9942614237269923
Q1 value of : KM_Travelled is 11.99
Q3 value of : KM_Travelled is 32.96
IQR value of : KM_Travelled is 20.97
Upper and Lower Limits of KM_Travelled is (-19.464999999999996, 64.41499999999999)

KM_Travelled has 0 outliers : []


**********************************************************



mean of : Price_Charged is 458.1819899811058
median of : Price_Charged is 425.06
median/mean ratio of : Price_Charged is 0.9277099696073352
Q1 value of : Price_Charged is 226.68
Q3 value of : Price_Charged is 633.88
IQR value of : Price_Charged is 407.2
Upper and Lower Limits of Price_Charged is (-384.11999999999995, 1244.6799999999998)

Price_Charged has 3240 outliers : [1341.17 1412.06 1540.61 ... 1282.89 1385.05 1406.5 ]


**********************************************************



mean of : Cost_of_Trip is 297.9220041400759
median of : Cost_of_Trip is 295.596
median/mean ratio of : Cost_of_Trip is 0.9921925735335002
Q1 value of : Cost_of_Trip is 158.4
Q3 value of : Cost_of_Trip is 432.432
IQR value of : Cost_of_Trip is 274.03200000000004
Upper and Lower Limits of Cost_of_Trip is (-252.64800000000005, 843.48)

Cost_of_Trip has 0 outliers : []


**********************************************************



mean of : Age is 35.34111205361856
median of : Age is 33.0
median/mean ratio of : Age is 0.9337566953165851
Q1 value of : Age is 25.0
Q3 value of : Age is 42.0
IQR value of : Age is 17.0
Upper and Lower Limits of Age is (-0.5, 67.5)

Age has 0 outliers : []


**********************************************************



mean of : Income_(USD/Month) is 15045.669816987705
median of : Income_(USD/Month) is 14676.0
median/mean ratio of : Income_(USD/Month) is 0.9754301522308884
Q1 value of : Income_(USD/Month) is 8439.0
Q3 value of : Income_(USD/Month) is 21023.0
IQR value of : Income_(USD/Month) is 12584.0
Upper and Lower Limits of Income_(USD/Month) is (-10437.0, 39899.0)

Income_(USD/Month) has 0 outliers : []


**********************************************************



mean of : Population is 3373228.31453213
median of : Population is 1595037.0
median/mean ratio of : Population is 0.4728517761837989
Q1 value of : Population is 671238.0
Q3 value of : Population is 8405837.0
IQR value of : Population is 7734599.0
Upper and Lower Limits of Population is (-10930660.5, 20007735.5)

Population has 0 outliers : []


**********************************************************



mean of : Users is 168473.24698104346
median of : Users is 144132.0
median/mean ratio of : Users is 0.8555186213999763
Q1 value of : Users is 80021.0
Q3 value of : Users is 302149.0
IQR value of : Users is 222128.0
Upper and Lower Limits of Users is (-253171.0, 635341.0)

Users has 0 outliers : []


**********************************************************

In [19]:
Out[19]:
Text(0, 0.5, 'Yellow Cab')
In [20]:
Out[20]:
Text(0, 0.5, 'Yellow Cab')
In [21]:
Out[21]:
Text(0, 0.5, 'Yellow Cab')
In [22]:
Out[22]:
<AxesSubplot:>
In [23]:
Out[23]:
<AxesSubplot:>
In [24]:
Out[24]:
Text(0.5, 1.0, 'KM_Travelled  - Cost_of_Trip')
In [25]:
Out[25]:
Text(0.5, 1.0, 'Price_Charged - Cost_of_Trip')
In [26]:
Out[26]:
Text(0.5, 1.0, 'Population  - Users')
In [27]:
Out[27]:
Text(0.5, 1.0, 'Users - Price_Charged')
In [28]:
Covariance for  KM_Travelled - Price_Charged : 2805.3070413080854
Covariance for  KM_Travelled - Cost_of_Trip : 1897.735748373699
Covariance for  Price_Charged - Cost_of_Trip : 37272.9490460031
Covariance for  Users - Population : 306082774585.6005
Covariance for  Population - Price_Charged : 297071855.0581954
Covariance for  Users - Price_Charged : 7777261.839139378
In [29]:
pearson correlation coefficient for  KM_Travelled - Price_Charged : 0.8357531580209352
pearson correlation coefficient for  KM_Travelled - Cost_of_Trip : 0.9818483823189879
pearson correlation coefficient for  Price_Charged - Cost_of_Trip : 0.8598117262915619
pearson correlation coefficient for  Users - Population : 0.9154903444758992
pearson correlation coefficient for  Population - Price_Charged : 0.32658917101925905
pearson correlation coefficient for  Users - Price_Charged : 0.28106053569196765
In [30]:
spearman rank coefficient coefficient for  KM_Travelled - Price_Charged : SpearmanrResult(correlation=0.8929579061229217, pvalue=0.0)
spearman rank coefficient coefficient for  KM_Travelled - Cost_of_Trip : SpearmanrResult(correlation=0.9845458363254245, pvalue=0.0)
spearman rank coefficient coefficient for  Price_Charged - Cost_of_Trip : SpearmanrResult(correlation=0.9135811393768479, pvalue=0.0)
spearman rank coefficient coefficient for  Users - Population : SpearmanrResult(correlation=0.8742482215995742, pvalue=0.0)
spearman rank coefficient coefficient for  Population - Price_Charged : SpearmanrResult(correlation=0.20756103314228547, pvalue=0.0)
spearman rank coefficient coefficient for  Users - Price_Charged : SpearmanrResult(correlation=0.1982681085669414, pvalue=0.0)
In [31]:
Yellow Cab76.4%Pink Cab23.6%
Yellow CabPink CabPink & Yellow Cab Firm Total Users Overview
In [32]:
ATLANTA GAAUSTIN TXBOSTON MACHICAGO ILDALLAS TXDENVER COLOS ANGELES CAMIAMI FLNASHVILLE TNNEW YORK NYORANGE COUNTYPHOENIX AZPITTSBURGH PASACRAMENTO CASAN DIEGO CASEATTLE WASILICON VALLEYTUCSON AZWASHINGTON DC010k20k30k40k50k60k70k80k90k
Pink CabYellow CabPink & Yellow Cab Firm Users Distribution Over CityUsers
In [33]:
NEW YORK NY27.8%CHICAGO IL15.8%LOS ANGELES CA13.4%WASHINGTON DC12.2%BOSTON MA8.26%SAN DIEGO CA5.7%SILICON VALLEY2.37%SEATTLE WA2.23%ATLANTA GA2.1%DALLAS TX1.95%MIAMI FL1.8%AUSTIN TX1.36%ORANGE COUNTY1.11%DENVER CO1.06%NASHVILLE TN0.838%SACRAMENTO CA0.659%PHOENIX AZ0.574%TUCSON AZ0.537%PITTSBURGH PA0.365%
NEW YORK NYCHICAGO ILLOS ANGELES CAWASHINGTON DCBOSTON MASAN DIEGO CASILICON VALLEYSEATTLE WAATLANTA GADALLAS TXMIAMI FLAUSTIN TXORANGE COUNTYDENVER CONASHVILLE TNSACRAMENTO CAPHOENIX AZTUCSON AZPITTSBURGH PATotal Users Overview by Cities
In [34]:
NEW YORK NY56.7%LOS ANGELES CA8.94%WASHINGTON DC7.08%CHICAGO IL6.87%BOSTON MA3.59%SAN DIEGO CA3.22%SILICON VALLEY2.67%DALLAS TX2.29%ATLANTA GA1.71%MIAMI FL1.54%SEATTLE WA1.23%AUSTIN TX1.07%ORANGE COUNTY0.926%DENVER CO0.806%PHOENIX AZ0.391%NASHVILLE TN0.303%TUCSON AZ0.284%SACRAMENTO CA0.238%PITTSBURGH PA0.173%
NEW YORK NYLOS ANGELES CAWASHINGTON DCCHICAGO ILBOSTON MASAN DIEGO CASILICON VALLEYDALLAS TXATLANTA GAMIAMI FLSEATTLE WAAUSTIN TXORANGE COUNTYDENVER COPHOENIX AZNASHVILLE TNTUCSON AZSACRAMENTO CAPITTSBURGH PATotal Market Profit Share by Cities
In [35]:
Yellow Cab89.2%Pink Cab10.8%
Yellow CabPink CabTotal Market Profit Share by Cab Firms
In [36]:
Male57.3%Female42.7%
MaleFemaleTotal Users Overview by Gender
In [37]:
FemaleMale020k40k60k80k100k120k140k160k
Pink CabYellow CabPink & Yellow Cab Firm Users Distribution Over GenderUsers
In [38]:
Card60%Cash40%
CardCashTotal Users Overview by Payment Method
In [39]:
40 > Age >= 25 (MIDDLE)47.4%65 >= Age >= 40 (OLD)30%25 > Age >= 18 (YOUNG)22.6%
40 > Age >= 25 (MIDDLE)65 >= Age >= 40 (OLD)25 > Age >= 18 (YOUNG)Total Users Overview by Age Groups
In [40]:
25 > Age >= 18 (YOUNG)40 > Age >= 25 (MIDDLE)65 >= Age >= 40 (OLD)020k40k60k80k100k120k
Pink CabYellow CabPink & Yellow Cab Firm Users Distributions by Age GroupsUsers
In [41]:
SACRAMENTO CA5.37%SILICON VALLEY5.36%ORANGE COUNTY5.34%NEW YORK NY5.34%BOSTON MA5.32%CHICAGO IL5.31%LOS ANGELES CA5.3%SAN DIEGO CA5.29%PHOENIX AZ5.28%MIAMI FL5.27%DENVER CO5.27%TUCSON AZ5.26%ATLANTA GA5.25%DALLAS TX5.22%SEATTLE WA5.22%NASHVILLE TN5.18%WASHINGTON DC5.18%AUSTIN TX5.17%PITTSBURGH PA5.07%
SACRAMENTO CASILICON VALLEYORANGE COUNTYNEW YORK NYBOSTON MACHICAGO ILLOS ANGELES CASAN DIEGO CAPHOENIX AZMIAMI FLDENVER COTUCSON AZATLANTA GADALLAS TXSEATTLE WANASHVILLE TNWASHINGTON DCAUSTIN TXPITTSBURGH PAAverage Income by Cities
In [42]:
Pink Cab50%Yellow Cab50%
Pink CabYellow CabAverage Income by Cab Firm
In [43]:
NEW YORK NY27.7%CHICAGO IL15.8%LOS ANGELES CA13.4%WASHINGTON DC12.2%BOSTON MA8.27%SAN DIEGO CA5.68%SILICON VALLEY2.39%SEATTLE WA2.23%ATLANTA GA2.08%DALLAS TX1.95%MIAMI FL1.79%AUSTIN TX1.35%ORANGE COUNTY1.1%DENVER CO1.06%NASHVILLE TN0.842%SACRAMENTO CA0.664%PHOENIX AZ0.565%TUCSON AZ0.533%PITTSBURGH PA0.366%
NEW YORK NYCHICAGO ILLOS ANGELES CAWASHINGTON DCBOSTON MASAN DIEGO CASILICON VALLEYSEATTLE WAATLANTA GADALLAS TXMIAMI FLAUSTIN TXORANGE COUNTYDENVER CONASHVILLE TNSACRAMENTO CAPHOENIX AZTUCSON AZPITTSBURGH PATotal KM Travelled by Cities
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Yellow Cab76.4%Pink Cab23.6%
Yellow CabPink CabTotal KM Travelled by Cab Firm
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LOS ANGELES CA5.26%ATLANTA GA5.26%AUSTIN TX5.26%CHICAGO IL5.26%DALLAS TX5.26%DENVER CO5.26%MIAMI FL5.26%NASHVILLE TN5.26%NEW YORK NY5.26%ORANGE COUNTY5.26%PHOENIX AZ5.26%PITTSBURGH PA5.26%SACRAMENTO CA5.26%SAN DIEGO CA5.26%SEATTLE WA5.26%SILICON VALLEY5.26%TUCSON AZ5.26%WASHINGTON DC5.26%BOSTON MA5.26%
LOS ANGELES CAATLANTA GAAUSTIN TXCHICAGO ILDALLAS TXDENVER COMIAMI FLNASHVILLE TNNEW YORK NYORANGE COUNTYPHOENIX AZPITTSBURGH PASACRAMENTO CASAN DIEGO CASEATTLE WASILICON VALLEYTUCSON AZWASHINGTON DCBOSTON MAAverage Profit per KM Travelled by Cities
In [46]:
Pink Cab50%Yellow Cab50%
Pink CabYellow CabAverage Profit per KM Travelled by Cab Firm
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Out[47]:
Transaction_ID Company City KM_Travelled Price_Charged Cost_of_Trip Customer_ID Payment_Mode Gender Age Income_(USD/Month) Population Users User_Pop_Ratio Profit_of_Trip Profit_per_KM Year_of_Travel Month_of_Travel Day_of_Travel
Date_of_Travel
1970-01-01 00:00:00.000042377 10000011 Pink Cab ATLANTA GA 30.45 370.95 313.6350 29290 Card Male 28 10813 814885 24701 0.030312 57.3150 6.081963 1970 1 1
1970-01-01 00:00:00.000043302 10351127 Yellow Cab ATLANTA GA 26.19 598.70 317.4228 29290 Cash Male 28 10813 814885 24701 0.030312 281.2772 6.081963 1970 1 1
1970-01-01 00:00:00.000043427 10412921 Yellow Cab ATLANTA GA 42.55 792.05 597.4020 29290 Card Male 28 10813 814885 24701 0.030312 194.6480 6.081963 1970 1 1
1970-01-01 00:00:00.000042375 10000012 Pink Cab ATLANTA GA 28.62 358.52 334.8540 27703 Card Male 27 9237 814885 24701 0.030312 23.6660 6.081963 1970 1 1
1970-01-01 00:00:00.000043211 10320494 Yellow Cab ATLANTA GA 36.38 721.10 467.1192 27703 Card Male 27 9237 814885 24701 0.030312 253.9808 6.081963 1970 1 1
1970-01-01 00:00:00.000043224 10324737 Yellow Cab ATLANTA GA 6.18 138.40 87.5088 27703 Cash Male 27 9237 814885 24701 0.030312 50.8912 6.081963 1970 1 1
1970-01-01 00:00:00.000043400 10395626 Pink Cab ATLANTA GA 13.39 167.03 141.9340 27703 Card Male 27 9237 814885 24701 0.030312 25.0960 6.081963 1970 1 1
1970-01-01 00:00:00.000042371 10000013 Pink Cab ATLANTA GA 9.04 125.20 97.6320 28712 Cash Male 53 11242 814885 24701 0.030312 27.5680 6.081963 1970 1 1
1970-01-01 00:00:00.000042634 10079404 Yellow Cab ATLANTA GA 39.60 704.30 494.2080 28712 Card Male 53 11242 814885 24701 0.030312 210.0920 6.081963 1970 1 1
1970-01-01 00:00:00.000042909 10186994 Yellow Cab ATLANTA GA 18.19 365.63 246.6564 28712 Card Male 53 11242 814885 24701 0.030312 118.9736 6.081963 1970 1 1
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201620172018−1−0.500.51
Cab CompaniesYellow CabPink CabTotal Profit per year by Cab FirmYearsProfits
In [51]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 359392 entries, 0 to 359391
Data columns (total 20 columns):
 #   Column              Non-Null Count   Dtype         
---  ------              --------------   -----         
 0   Transaction_ID      359392 non-null  int64         
 1   Date_of_Travel      359392 non-null  datetime64[ns]
 2   Company             359392 non-null  category      
 3   City                359392 non-null  category      
 4   KM_Travelled        359392 non-null  float64       
 5   Price_Charged       359392 non-null  float64       
 6   Cost_of_Trip        359392 non-null  float64       
 7   Customer_ID         359392 non-null  int64         
 8   Payment_Mode        359392 non-null  category      
 9   Gender              359392 non-null  category      
 10  Age                 359392 non-null  int64         
 11  Income_(USD/Month)  359392 non-null  int64         
 12  Population          359392 non-null  int64         
 13  Users               359392 non-null  int64         
 14  User_Pop_Ratio      359392 non-null  float64       
 15  Profit_of_Trip      359392 non-null  float64       
 16  Profit_per_KM       359392 non-null  float64       
 17  Year_of_Travel      359392 non-null  int64         
 18  Month_of_Travel     359392 non-null  int64         
 19  Day_of_Travel       359392 non-null  int64         
dtypes: category(4), datetime64[ns](1), float64(6), int64(9)
memory usage: 56.0 MB
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